๐Ÿ”ฅ ExSan Pushing the Limits of High-Frequency Trading with C++ ๐Ÿ”ฅ

High-Frequency Trading with C++ — Blog Update

In the initial implementation, a new cluster was created each time new data was read from the simulator's data stream. I observed that this approach resulted in significant time consumption due to the repeated creation and deletion of clusters. To address this, I developed a method to reuse the originally created cluster, substantially reducing overhead. The method for this improved version is quite simple: the clusters are declared static from the beginning, allowing them to persist and be reused. Because of the nature of the clusters — they are implemented as Red-Black Trees — if there are not enough nodes to accommodate new data, the code simply adds additional nodes dynamically, allowing for seamless expansion. This optimization was applied while feeding ExSan with my market simulator, which mimics the asynchronicity of real market data over time, enabling efficient and realistic backtesting of trading strategies. As a result, the throughput of data processing increased, and the overall efficiency of the program improved considerably.

๐Ÿง  Algorithm for Large-Scale Sparse Covariance Matrix

Optimizing Covariance and Correlation for ultra-low-latency environments using clustered data structures.

I’m currently developing my own HFT algorithm with a clear goal: to optimize Covariance and Correlation performance in ultra-low-latency environments using clustered data structures.

This has been one of the most technically challenging and rewarding parts of the project so far—and I’m excited to share what I’ve built:

The current implementation performs well—but after redesigning clusters as a static abstract data structure, I’ve seen a major boost in data processing throughput. I’ll be sharing those results soon.

In parallel, I’ve also built and beta-tested my own trading platform, fully integrated with Interactive Brokers using C++.

This is more than code—it's a personal mission. And I’m just getting started.

For clarity, this implementation relies solely on raw pointers—no smart pointers or abstractions.

๐Ÿง  Welcome to ExSan - Not Afraid of Pointers๐Ÿง 

Author

Tags:
#HFT #Cplusplus #QuantFinance #AlgorithmicTrading #FinTech #TradingSystems #LowLatency #InteractiveBrokers

iX         exsan.plusplus@gmail.com    ilinkedIn

Flag Counter

Comments

Popular posts from this blog

Roberto Santander - Resume

Inside the Engine: A Code-Level Look at ExSan CODE’s Processing Clusters